11 resultados para QUINONE POOL
em Repositório Científico do Instituto Politécnico de Lisboa - Portugal
Resumo:
The study’s main purpose was the assessment of the environmental fungal contamination, the exploration of possible associations between related environmental variables and the study of the relationship between fungal contamination of air and surfaces. A descriptive study was developed based upon air and surfaces monitoring for fungal contamination in ten indoor gymnasiums with a swimming pool located in Lisbon’s urban area. Fifty 200 litres air samples and 120 surface swabs were collected. Surfaces samples were collected before and after cleaning and disinfection and temperature and relative humidity values were registered during the collection period. Twenty five different species of fungi were identified in the air samples, being the three most commonly isolated genera the following: Cladosporium (36.6%), Penicillium (19.0%) and Aspergillus (10.2%). Thirty-seven different species of fungi were identified in the surface samples. Fusarium sp. was the most frequent genera before (19.1%) and after (17.2%) cleaning and disinfection. There was a significant association between the numbers of visitors and the fungal contamination determined in the surface samples (p<0.05). There was no significant association (p>0.05) between the contamination encountered in the air samples and the one registered in the surface samples and between the fungal contamination and the temperature or relative humidity measured on location. The data obtained enabled the assessment of the establishment’s fungal contamination and led the authors to conclude, consequently, that physical activity, which generally promotes health, can in fact be challenged by this factor.
Resumo:
The electricity industry throughout the world, which has long been dominated by vertically integrated utilities, has experienced major changes. Deregulation, unbundling, wholesale and retail wheeling, and real-time pricing were abstract concepts a few years ago. Today market forces drive the price of electricity and reduce the net cost through increased competition. As power markets continue to evolve, there is a growing need for advanced modeling approaches. This article addresses the challenge of maximizing the profit (or return) of power producers through the optimization of their share of customers. Power producers have fixed production marginal costs and decide the quantity of energy to sell in both day-ahead markets and a set of target clients, by negotiating bilateral contracts involving a three-rate tariff. Producers sell energy by considering the prices of a reference week and five different types of clients with specific load profiles. They analyze several tariffs and determine the best share of customers, i.e., the share that maximizes profit. © 2014 IEEE.
Resumo:
The electricity industry throughout the world, which has long been dominated by vertically integrated utilities, has experienced major changes. Deregulation, unbundling, wholesale and retail wheeling, and real-time pricing were abstract concepts a few years ago. Today market forces drive the price of electricity and reduce the net cost through increased competition. As power markets continue to evolve, there is a growing need for advanced modeling approaches. This article addresses the challenge of maximizing the profit (or return) of power producers through the optimization of their share of customers. Power producers have fixed production marginal costs and decide the quantity of energy to sell in both day-ahead markets and a set of target clients, by negotiating bilateral contracts involving a three-rate tariff. Producers sell energy by considering the prices of a reference week and five different types of clients with specific load profiles. They analyze several tariffs and determine the best share of customers, i.e., the share that maximizes profit. © 2014 IEEE.
Resumo:
Cellulose and its derivatives, such as hydroxypropylcellulose (HPC) have been studied for a long time but they are still not well understood particularly in liquid crystalline solutions. These systems can be at the origin of networks with properties similar to liquid crystalline (LC) elastomers. The films produced from LC solutions can be manipulated by the action of moisture allowing for instance the development of a soft motor (Geng et al., 2013) driven by humidity. Cellulose nanocrystals (CNC), which combine cellulose properties with the specific characteristics of nanoscale materials, have been mainly studied for their potential as a reinforcing agent. Suspensions of CNC can also self-order originating a liquid-crystalline chiral nematic phases. Considering the liquid crystalline features that both LC-HPC and CNC can acquire, we prepared LC-HPC/CNC solutions with different CNC contents (1,2 and 5 wt.%). The effect of the CNC into the LC-HPC matrix was determined by coupling rheology and NMR spectroscopy - Rheo-NMR a technique tailored to analyse orientational order in sheared systems. (C) 2015 Elsevier Ltd. All rights reserved.
Resumo:
Esta dissertação, apresenta um simulador multi-agente para o mercado eléctrico. Neste simulador agentes heterogéneos, racionalmente limitados e com capacidade de aprendizagem, co-evoluem dinamicamente. O modelo de mercado apresentado é inspirado no mercado diário do MIBEL. É um modelo Pool, gerido por uma entidade operadora de mercado, onde compradores e vendedores podem licitar energia. No lado vendedor, empresas produtoras licitam a energia das suas unidades produtoras em pares quantidadepre ço. Por outro lado, uma vez que o cenário simulado é um mercado de venda, o comprador apresenta uma procura xa, i.e., submete apenas quantidades de energia. Todas as entidades do mercado eléctrico são vistas no sistema multi-agente, modelado através da plataforma INGENIAS, como agentes autónomos. Pelos resultados obtidos nas experiências feitas, confere-se que o simulador é uma ferramenta de apoio à tomada de decisão, pois ajuda a compreender o comportamento emergente do mercado e avalia o impacto das acções escolhidas, manualmente, pelo utilizador ou, automaticamente, atrav és da aprendizagem por reforço. A aprendizagem por reforço visa facilitar a tomada de decisão humana na venda de energia, licitando a energia das unidades produtoras de forma a maximizar os lucros.
Resumo:
Fungal contamination of air in 10 gymnasiums with swimming pools was monitored. Fifty air samples of 200 L each were collected, using a Millipore air tester, from the area surrounding the pool, in training studios, in showers and changing rooms for both sexes, and also, outside premises, since these are the places regarded as reference. Simultaneously, environmental parameters – temperature and humidity – were also monitored. Some 25 different species of fungi were identified. The six most commonly isolated genera were the following: Cladosporium sp. (36.6%), Penicillium sp. (19.0%), Aspergillus sp. (10.2%), Mucor sp. (7%), Phoma sp. and Chrysonilia sp. (3.3%). For yeasts, three different genera were identified, namely, Rhodotorula sp. (70%), Trichosporon mucoides and Cryptococcus uniguttulattus (10%).
Resumo:
A energia eléctrica é um bem essencial para a maioria das sociedades. O seu fornecimento tem sido encarado como um serviço público, da responsabilidade dos governos, através de empresas monopolistas, públicas e privadas. O Mercado Ibérico de Electricidade (MIBEL) surge com o objectivo da integração e cooperação do sector eléctrico Português e Espanhol, no qual é possível negociar preços e volumes de energia. Actualmente, as entidades podem negociar através de um mercado bolsista ou num mercado de contratos bilaterais. Uma análise dos mercados de electricidade existentes mostra que estes estão longe de estarem liberalizados. As tarifas não reflectem o efeito da competitividade. Além disso, o recurso a contratos bilaterais limita frequentemente os clientes a um único fornecedor de energia eléctrica. Nos últimos anos, têm surgido uma série de ferramentas computacionais que permitem simular, parte ou a totalidade, dos mercados de electricidade. Contudo, apesar das suas potencialidades, muitos simuladores carecem de flexibilidade e generalidade. Nesta perspectiva, esta dissertação tem como principal objectivo o desenvolvimento de um simulador de mercados de energia eléctrica que possibilite lidar com as dificuldades inerentes a este novo modelo de mercado, recorrendo a agentes computacionais autónomos. A dissertação descreve o desenho e a implementação de um simulador simplificado para negociação de contratos bilaterais em mercados de energia, com particular incidência para o desenho das estratégias a utilizar pelas partes negociais. Além disso, efectua-se a descrição de um caso prático, com dados do MIBEL. Descrevem-se também várias simulações computacionais, envolvendo retalhistas e consumidores de energia eléctrica, que utilizam diferentes estratégias negociais. Efectua-se a análise detalhada dos resultados obtidos. De forma sucinta, os resultados permitem concluir que as melhores estratégias para cada entidade, no caso prático estudado, são: a estratégia de concessões fixas, para o retalhista, e a estratégia de concessões baseada no volume de energia, para o consumidor.
Resumo:
A liberalização do sector eléctrico, e a consequente criação de mercados de energia eléctrica regulados e liberalizados, mudou a forma de comercialização da electricidade. Em particular, permitiu a entrada de empresas nas actividades de produção e comercialização, aumentando a competitividade e assegurando a liberdade de escolha dos consumidores, para decidir o fornecedor de electricidade que pretenderem. A competitividade no sector eléctrico aumentou a necessidade das empresas que o integram a proporem preços mais aliciantes (do que os preços propostos pelos concorrentes), e contribuiu para o desenvolvimento de estratégias de mercado que atraiam mais clientes e aumentem a eficiência energética e económica. A comercialização de electricidade pode ser realizada em mercados organizados ou através de contratação directa entre comercializadores e consumidores, utilizando os contratos bilaterais físicos. Estes contratos permitem a negociação dos preços de electricidade entre os comercializadores e os consumidores. Actualmente, existem várias ferramentas computacionais para fazer a simulação de mercados de energia eléctrica. Os simuladores existentes permitem simulações de transacções em bolsas de energia, negociação de preços através de contratos bilaterais, e análises técnicas a redes de energia. No entanto, devido à complexidade dos sistemas eléctricos, esses simuladores apresentam algumas limitações. Esta dissertação apresenta um simulador de contratos bilaterais em mercados de energia eléctrica, sendo dando ênfase a um protocolo de ofertas alternadas, desenvolvido através da tecnologia multi-agente. Em termos sucintos, um protocolo de ofertas alternadas é um protocolo de interacção que define as regras da negociação entre um agente vendedor (por exemplo um retalhista) e um agente comprador (por exemplo um consumidor final). Aplicou-se o simulador na resolução de um caso prático, baseado em dados reais. Os resultados obtidos permitem concluir que o simulador, apesar de simplificado, pode ser uma ferramenta importante na ajuda à tomada de decisões inerentes à negociação de contratos bilaterais em mercados de electricidade.
Resumo:
The general transcription factor TFIIB, encoded by SUA7 in Saccharomyces cerevisiae, is required for transcription activation but apparently of a specific subset of genes, for example, linked with mitochondrial activity and hence with oxidative environments. Therefore, studying SUA7/TFIIB as a potential target of oxidative stress is fundamental. We found that controlled SUA7 expression under oxidative conditions occurs at transcriptional and mRNA stability levels. Both regulatory events are associated with the transcription activator Yap1 in distinct ways: Yap1 affects SUA7 transcription up regulation in exponentially growing cells facing oxidative signals; the absence of this activator per se contributes to increase SUA7 mRNA stability. However, unlike SUA7 mRNA, TFIIB abundance is not altered on oxidative signals. The biological impact of this preferential regulation of SUA7 mRNA pool is revealed by the partial suppression of cellular oxidative sensitivity by SUA7 overexpression, and supported by the insights on the existence of a novel RNA-binding factor, acting as an oxidative sensor, which regulates mRNA stability. Taken together the results point out a primarily cellular commitment to guarantee SUA7 mRNA levels under oxidative environments.
Resumo:
Electricity markets are systems for effecting the purchase and sale of electricity using supply and demand to set energy prices. Two major market models are often distinguished: pools and bilateral contracts. Pool prices tend to change quickly and variations are usually highly unpredictable. In this way, market participants often enter into bilateral contracts to hedge against pool price volatility. This article addresses the challenge of optimizing the portfolio of clients managed by trader agents. Typically, traders buy energy in day-ahead markets and sell it to a set of target clients, by negotiating bilateral contracts involving three-rate tariffs. Traders sell energy by considering the prices of a reference week and five different types of clients. They analyze several tariffs and determine the best share of customers, i.e., the share that maximizes profit. © 2014 IEEE.
Resumo:
This paper is on the self-scheduling problem for a thermal power producer taking part in a pool-based electricity market as a price-taker, having bilateral contracts and emission-constrained. An approach based on stochastic mixed-integer linear programming approach is proposed for solving the self-scheduling problem. Uncertainty regarding electricity price is considered through a set of scenarios computed by simulation and scenario-reduction. Thermal units are modelled by variable costs, start-up costs and technical operating constraints, such as: forbidden operating zones, ramp up/down limits and minimum up/down time limits. A requirement on emission allowances to mitigate carbon footprint is modelled by a stochastic constraint. Supply functions for different emission allowance levels are accessed in order to establish the optimal bidding strategy. A case study is presented to illustrate the usefulness and the proficiency of the proposed approach in supporting biding strategies. (C) 2014 Elsevier Ltd. All rights reserved.